Unsplash · Pietro JengAI

A hands-on look at actually adjusting a model's weights instead of just steering it with prompts or feeding it fresh context through RAG. This course covers when fine-tuning is genuinely worth the cost, how parameter-efficient methods like LoRA make it practical, and how to build a dataset, run a training job, and evaluate the result honestly. Built for learners who already understand prompting and RAG and want the next tool in the toolkit.